Method for reconstructing signals

A signal and signal reconstruction technology, applied in the field of wireless communication, can solve problems such as large matrix order, increased computational complexity, and difficulty in application and promotion

Inactive Publication Date: 2014-06-25
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

[0007] The algorithm using eigenbasis combined with Bayesian compressed sensing needs to invert the matrix. In particular, the eigenexpansion basis needs to use the statistical characteristics of the signal to improve the recovery ability of the signal. The length of the signal is relatively long, and the order of the

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[0034] S1, the original signal Evenly divided into L segments, the length of each segment of the signal is equal and is an integer greater than 1, using a complete base Ψ makes the signal sparse in Ψ, each segment of the signal can be expanded in the same complete base, each segment of the signal Corresponding to different expansion coefficients , where Ψ is an orthogonal square matrix composed of characteristic basis vectors, L>1, and L is a natural number, a complete basis is a special matrix, and the column vectors of the matrix are linearly independent, and any signal can be It is represented by the linear sum of the column vectors in this matrix and the corresponding expansion coefficients. The eigenbasis vector refers to the eigenvector obtained after the eigenvalue decomposition of the matrix. These vectors are linearly independent and can be used to form a complete basis. Among them, Expand the coefficient range, which is a real number in [0.1,0], and the coefficien...

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Abstract

The invention belongs to the technical field of wireless communications, and particularly relates to a method for reconstructing signals in an ultra-wide-band communication system by the adoption of a low-complexity improved Bayes compressed sensing algorithm. The method comprises the steps that firstly, sectioning and filtering are conducted on received signals, then a measuring matrix is used for conducting linear combination on the filtered signals again, after a series of relatively simple iterative operations, the expansion coefficient of original signals under the characteristic base can be measured, and therefore reconstruction of the original signals is realized. According to the method for reconstructing the signals, on one hand, the Bayes compressed sensing algorithm is improved by fully utilizing the characteristics of the characteristic base, the restorability is improved, more importantly, the complex matrix inversion process in the Bayes compressed sensing algorithm is avoided, and particularly, when the length of the signals is large and the order of the matrix is large, the signal restoration operation complexity can be effectively lowered.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a method for reconstructing a signal by using a low-complexity improved Bayesian compressed sensing algorithm in an ultra-wideband communication system. Background technique [0002] Since UWB (Ultra Wideband) signals are mostly narrow pulse signals in the time domain, their frequency domain bandwidth is too wide. According to the requirements of the Nyquist sampling law, the sampling rate will be as high as several GHz, so that the analog-to-digital converter The design brings huge challenges, and a large amount of data processing brings a great burden to the digital signal processor, the current hardware level is difficult to achieve the above requirements. Compressed sensing (CS, Compressed sensing), as a novel low-speed signal sampling theory, breaks through the limitation of Nyquist sampling law. Some literatures have carried out theoretical resear...

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Application Information

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IPC IPC(8): H03M7/30
Inventor 王梦瑶成先涛袁波岳光荣李少谦
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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